Comparative Study Between Raw and Different Processed Stellera chamaejasme L. Based on Electronic Eye, Electronic...

Langdu (SSC) is the dried root of Stellera chamaejasme L. Due to its toxicity, the milk-processed (NSC), Terminalia chebula decoction-processed (HSC), wine-processed (JSC), and vinegar-processed (CSC) products are predominantly employed in clinical practice.

To illuminate the difference in color, volatile, and non-volatile compounds among the processed products of SC.

SC was processed into five products. Color characteristics, volatile, and non-volatile compounds were systematically analyzed using electronic eye, electronic nose, and HPLC analyses. Multivariate statistical analyses comprising principal component analysis (PCA), hierarchical cluster analysis (HCA), discriminant factor analysis (DFA), partial least squares discriminant analysis (PLS-DA), and correlation analysis were performed.

Following processing, significant differences in color, volatile, and non-volatile components were observed. The established chemometric models demonstrated rapid discriminative capability to the five products, with seven volatile components and 16 non-volatile components identified as potential chemical markers. Quantitative analysis revealed increased levels of daphnetin and scopoletin and decreased levels of bergenin and chamaechromone after processing. Pearson's correlation analysis revealed significant positive correlations between the lightness (L*) value in the CIELAB color space and scopoletin (p < 0.001) or 7-hydroxycoumarin (p < 0.001), while the b* (yellow-blue) axis showed significant positive correlations with daphnetin (p < 0.001) and isopimpinellin (p < 0.05) contents. Additionally, a* (red-green) axis showed significant negative correlations with daphnetin, 7-hydroxycoumarin, and daphnoretin levels (p < 0.01).

The established models efficiently, accurately, and reliably discriminated the different processed products of SC through multidimensional characterization. These potential chemical markers and correlation patterns provide the scientific foundation for toxicity reduction assessment and processing standardization.